Traffic congestion is a huge problem in urban areas. In Stockholm, car owners spend about 16 workdays stuck in traffic each year. Public transport is also affected by this, and during rush hours, bus services can suffer huge delays.
The objective of the Spatial Modelling Analytics & Real-time Tracking (SMART) Mobility Project is to mitigate growing urban traffic congestion challenges and associated issues of environmental degradation, economic inefficiency and negative impacts to the quality of life of citizens.
SMART Mobility will revolutionise the efficiency of traffic and commuting in cities by leveraging the capabilities of new 4D spatial technology and analysis platforms using real-time vehicle location and various movement data.
Several data sets
The project will use data from many different sources, including:
- Wifi data from Bumbee Labs. Position data is collected when smartphone searches for WiFi-connectivity. Bumbee Labs technologies utilizes this for crowd measurements and pedestrian flow, which is compliant with GDPR regulations.
- Vehicle data from Ramboll, Inrix and Tomtom. Through GPS, data such as speed and route can be obtained.
- Crowd data from Tre. Anonymize crowd data obtained from different sources, like cellular data and WiFi.
The platform will be open and transparent for information and data exchange. The data sets can then be used for new types of services and applications, such as new routes for public transport and analyzing the size of a bus fleet. Through visualisation, this can be used to plan for a more effective public transport. In the end, this will benefit the end users – the travellers.
The project aims to:
- Conduct three use cases in the Kista-Järva area
- Build the SMART-platform
- Integrate data sets into the platform
The anticipated result of the project is to completely integrate siloed data using 4D location. A real-time, shared and collaborative application platform will give access to multiple stakeholders. Furthermore, SMART will optimize mobility in the existing transportation network on a massive scale.
Urban ICT Arena
Use Case 1: Measurements on board
Most people who travel by bus have a smartphone with them, and many of these have a wifi turned on. This can be used to see how many people travel, which transport routes are most frequently used, which partial journeys take place and where transfers are made.
Use Case 2: Public transport hubs
Public transport nodes are useful for information gathering, both in terms of positioning equipment, multisensors, cellular and wireless networks and various mobile services that naturally allow positioning. Especially in cities where it is denser between base stations for mobile networks, it opens up to more accurately classify the type of context a user is in. The project will look at Helenelund Station and Kista bus terminal.
Use Case 3: Links to social distancing (in conjunction with COVID-19)
If you know which buses, subways and trains are more populated, it is easier for the traveler to take responsibility for their own distancing in the public space, practically be able to travel earlier or later, choose another route or mode of transport, or as a base to assess whether or not to undertake a trip at a particular time.